test

scraibe/test/test_audio.py

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+import pytest
+#from scraibe import Transcriber
+#from unittest.mock import patch, mock_open
+#import unittest
+#import os
+from .audio import AudioProcessor
+import torch
+
+
+
+
+
+test_waveform = torch.tensor([]).to('cuda')
+test_sr = 16000
+SAMPLE_RATE = 16000
+NORMALIZATION_FACTOR = 32768
+
+
+@pytest.fixture
+def probe_audio_processor():
+    return AudioProcessor(test_waveform, test_sr)
+
+
+
+
+
+
+def test_AudioProcessor_init(probe_audio_processor):
+    assert isinstance(probe_audio_processor, AudioProcessor)
+    assert probe_audio_processor.waveform.device == test_waveform.device
+    assert torch.equal(probe_audio_processor.waveform, test_waveform)
+    assert probe_audio_processor.sr == test_sr
+
+
+
+def test_cut():
+    waveform = torch.Tensor(10, 3)
+    sr = 16000
+    start = 4
+    end = 7
+    assert AudioProcessor(waveform, sr).cut(start, end).size() == int((end - start) * test_sr)
+
+
+
+""" def test_cut(probe_audio_processor):
+    start = 10
+    end = 100
+    test_segment =  probe_audio_processor.cut(start, end) 
+    print(test_segment)
+    erwartetes_segment = int((end - start) * test_sr)
+    print(test_segment.size())
+    assert len(test_segment) == erwartetes_segment
+ """
+
+
+
+
+
+def test_audio_processor_invalid_sr():
+    with pytest.raises(ValueError):
+        AudioProcessor(test_waveform, [44100,48000])
+
+
+def test_audio_processor_SAMPLE_RATE():
+    probe_audio_processor = AudioProcessor(test_waveform)
+    assert probe_audio_processor.sr == SAMPLE_RATE       
+
+
+
+
+
+
+
+
+
+
+
+  
+
+
+    
+
+